Hyperscalers List GPUs at Nearly 2× the GPU-Cloud Price, Fluence Research Finds

The AI Compute Race report costs GPU compute exterior the largest consumers: a three-year dedication cuts the median value by 48%, whereas 17 of twenty-two tracked GPU fashions rose in value over the previous yr

DALLAS, Texas – November 13, 2026 – Fluence has revealed The AI Compute Race, a report that costs GPU cloud compute for each firm that isn’t a frontier lab or a hyperscaler. It was produced with analysis companions NEAR AI, io.net, Boundless, Phala, Gensyn, Fortytwo, Theta, Compute Labs and GAIB. Its central discovering: the place an organization buys a GPU-hour units the worth. Throughout H100, H200 and B200 fashions, hyperscalers listing GPUs at 1.98 occasions the GPU-cloud median, from 1.4 occasions on the B200 to 2.8 occasions on the H100. The identical H200 lists from $4.08 to $10.60 an hour.

Dedication size issues virtually as a lot as supplier alternative. In opposition to every supplier’s personal on-demand fee, a one-year reservation cuts the median value by 21% and a three-year time period by 48%. Spot capability lists at 53% of on-demand, for workloads that may be interrupted.

Patrons who count on GPU costs to fall might must recheck their budgets. Seventeen of the 22 GPU fashions tracked by GetDeploying value greater than a yr earlier, and the median H100 rents for 13% to 30% extra, relying on the window measured.

The report additionally traces why costs are quickly rising:

• Demand moved to open fashions. Chinese language fashions’ share of OpenRouter tokens amongst corporations within the US, Europe and the World South rose from 6–13% to 57–67% in beneath eight months, based on CNBC. Open weights let any firm with GPUs serve a near-frontier mannequin on {hardware} it controls.
• The largest consumers locked up the latest provide. The 4 largest hyperscalers information $720–740 billion of 2026 capital spending, and the 4 largest disclosed offers by AI labs and Meta with neoclouds whole about $233 billion, three of them “as much as” quantities and far of it for capability not but delivered.
• The GPU-hour is changing into a monetary asset. CME, ICE and Nodal Alternate have introduced GPU futures, every deciding on a special value index, whereas lenders are already lending towards GPUs: Lambda’s investment-grade-rated mortgage priced at 6.78% and Sharon AI’s, with no ranking disclosed, at 9.95%.

“Open-weight fashions are shut behind the perfect closed ones, and firms are switching to them. Any firm with GPUs can now serve a near-frontier mannequin on {hardware} it controls. The GPUs are the arduous half,” mentioned Evgeny Ponomarev, Co-founder of Fluence.

The report closes with 4 methods to pay much less for a similar compute: examine the identical chip throughout supplier varieties, commit when the workload is regular, match the GPU technology to the mannequin, and look past the hyperscalers, since a lot of the latest neocloud capability is contracted to labs years forward.

The total report is out there at fluence.ai/compute-race-2026.

About Fluence

Fluence Cloud is a GPU cloud supplier with capability from unbiased knowledge facilities (fluence.ai). Based in 2017 by Dmitry Kurinskiy, Evgeny Ponomarev and Tom Trowbridge, the corporate has raised $14 million from buyers together with 1KX, Multicoin, Distributed World, Blockchange, Tiger World and Protocol Labs.